INTELLIGENT VISION SYSTEMS ENT 496 Lecture 1 Ms

INTELLIGENT VISION SYSTEMS ENT 496 Lecture 1. Ms. HEMA C. R. IVS and its Components Hema –ENT 496– Lecture 1

• What is Intelligent Vision Road Map • Image and Vision • Intelligent Vision Systems • Components of an Intelligent Vision System [IVS] • Applications of vision systems • Advantages of IVS • Vision Optics • Frame Grabbers • Lighting and Illumination Hema –ENT 496– Lecture 1 2

Intelligent Vision Why do Machine/ Robots need vision? – Vision is provided to enhance the component of Intelligence Why is Vision important? – About 70% of our intelligence is from derived from vision. – The remaining 30% from sound. Hema –ENT 496– Lecture 1 3

Intelligent Vision • Intelligent Vision is the application of computer vision to industry. • It is a subfield of engineering that encompasses – – Computer science, Optics Mechanical engineering and Industrial automation. • One of the most common applications of IVS is the inspection of manufactured goods such as semiconductor chips, automobiles, food and pharmaceuticals. • Bio-mementics is changing all this and vision applications are now being designed to serve Hema –ENT 496– 4 the community Lecture 1

Image and Vision • Image – Images are two-dimensional projections of the three-dimensional world • Vision – Vision is the most Complex of human senses, about a fourth of the brain’s volume is devoted to it. • Image Processing – Processing images to give new images • Computer Vision – Deals with what the images mean – aims to interpret images • Intelligent Vision – Apply vision and image processing • Vision System – A Vision System recovers useful information about a scene from its two dimensional projections Hema –ENT 496– Lecture 1 5

Intelligent Vision Systems • Characteristics – Ability to extract pertinent information from a background of irrelevant details – The capacity to learn from examples and apply to new situations – Ability to infer facts from incomplete information – Capability to generate self motivated goals and formulate plans for meeting these goals. Hema –ENT 496– Lecture 1 6

Components of a Intelligent Vision System – Input source • objects, scene, prints etc – Optics • sensors, digital cameras – Lighting • illumination levels – A part sensor [optional] • to indicate presence of objects – A frame grabber • stores images & interface – PC platform [optional] – Inspection software • Image processing algorithms Digital I/O Hema –ENT 496– – Lecture 1 • Display, Print, Interface 7

Vision System Portrayal Hema –ENT 496– Lecture 1 8

Operations to be performed by IVS • Describe images, objects and physical world – Mathematical models of image and objects and knowledge representation • Image Processing – Improves image for human and computer consumption, highlight / extract relevant feature The Ultimate Aim of a Vision System is to recognize objects • Segmentation within edge, regions, surfaces etc. – Extract features such aa image • Pattern Recognition – Classify the images • Measurement Analysis – Measure features on the object • Image Understanding – Locate objects in the image, classify them and build 3 D Hema –ENT 496– models 9 Lecture 1

Applications of Intelligent Vision Systems • • Large-scale industrial manufacture Safety systems in industrial environments Inspection of pre-manufactured objects Visual stock control and management systems (counting, barcode reading, store interfaces for digital systems) • Control of Automated Guided Vehicles (AGVs) • Automated monitoring of sites for security and safety Hema –ENT 496– Lecture 1 10

Applications of an Intelligent Vision System • Monitoring of agricultural production • Quality control and refinement of food products • Retail automation • Consumer equipment control • Medical imaging processes (e. g. Interventional Radiology) • Medical remote examination and procedures Hema –ENT 496– Lecture 1 11

Autonomous Vehicles Transport Safety Aerial Navigation Hema –ENT 496– Lecture 1 12

The Human Face Head Modeling Face Recognition Hema –ENT 496– Lecture 1 13

Industrial Inspection Detecting Objects Intelligent parts Hema –ENT 496– Lecture 1 14

Medical Images Chromosomes Brain MRI Hema –ENT 496– Lecture 1 15

Remote Sensing Land Management Crop Classification Hema –ENT 496– Lecture 1 16

Surveillance Intruder Monitoring People Tracking Hema –ENT 496– Lecture 1 17

Transport Number Plate Traffic Control Hema –ENT 496– Lecture 1 Hema –ENT 496 – Lecture 1 18

Advantages of IVS in Industries • Cutting out defective goods • Making better use of raw materials • Cutting the cost of quality control • Enabling real-time process monitoring • Improving employment conditions Hema –ENT 496– Lecture 1 19

Vision Optics • A Cognex In-Sight Vision Sensor • • • Hema –ENT 496– Lecture 1 Vision Systems – Stand alone – PC based Smart Camera – Self contained [no pc req. ] • CCD image sensors Neural Network-Based • CMOS image sensors Zi. CAMs from JAI Pulnix Vision Sensors – Integrated devices Compact Vision System – No programming required from National Instruments – Between smart cams and vision systems Digital Cameras – CCD image – CMOS image – Flash memory – Memory stick – Smart. Media cards 20 – Removable [microdrives, CD, DVD]

Imaging Sensors • Image sensors convert light into electric charge and process it into electronic signals • Image Sensors – Charge Coupled Device CCD • All pixels are devoted to light capture • Output is uniform • High image quality • Used in cell phone cameras – Complementary Metal Oxide Semiconductor CMOS • Pixels devoted to light capture are limited • Output is not uniform • High Image quality • Used in professional and industrial cameras Hema –ENT 496– Lecture 1 21

Frame Grabbers • A frame grabber is a device to acquire [grab] and convert analog to digital images. Modern FG have many additional features like more storage, multiple camera links etc. Hema –ENT 496– Lecture 1 22

Frame Grabbers • A typical frame grabber consists of – a circuit to recover the horizontal and vertical synchronization pulses from the input signal; – An analog to digital converter – a colour decoder circuit, a function that can also be implemented in software – some memory for storing the acquired image (frame buffer) – a bus interface through which the main processor can control the acquisition and access the data. Hema –ENT 496– Lecture 1 23

Lighting • Correct lighting is the single most important design parameter in a vision system • Selection of a light source for a vision application is governed by three factors: – The type of features that must be captured by the vision system – The need for the part to be either moving or stationary when the image is captured. – The degree of visibility of the environment in which the image is captured. Hema –ENT 496– Lecture 1 24

Lighting Techniques • The three lighting techniques used in vision applications are: – Front lighting, – Back lighting – Structured lighting Hema –ENT 496– Lecture 1 25

Front Lighting Sources Ring Shape Lighting to detect loose caps Spot Lighting to check chip orientation in embossed tape Tube Lighting to detect stains on sheets Hema –ENT 496– Lecture 1 Area type lighting to detect hole position in lead frames 26

Interesting Links Visit http: //www. Intelligentvisiononline. org http: //www. eeng. dcu. e/~whelanp/proverbs. pdf to understand vision systems better References: http: //www. bmva. ac. uk/apps/ http: //en. wikipedia. org www. Intelligentvisiononline. org http: //homepages. inf. ed. ac. uk/rbf/CVonline Hema –ENT 496– Lecture 1 27

IVS and its Components End of Lecture 1 Hema –ENT 496– Lecture 1